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        <h1 id="Learn-to-Rank"><a href="#Learn-to-Rank" class="headerlink" title="Learn to Rank"></a>Learn to Rank</h1><p><font color=#999AAA >Learn to Rank（机器学习排序）简称为LTR或者L2R</p>
<span id="more"></span> 

<hr>
<h1 id="1-前言"><a href="#1-前言" class="headerlink" title="1 前言"></a>1 前言</h1><h2 id="1-1-Learn-to-rank-的提出背景"><a href="#1-1-Learn-to-rank-的提出背景" class="headerlink" title="1.1 Learn to rank 的提出背景"></a>1.1 Learn to rank 的提出背景</h2><h2 id="1-2-Learn-to-rank-的基本框架"><a href="#1-2-Learn-to-rank-的基本框架" class="headerlink" title="1.2 Learn to rank 的基本框架"></a>1.2 Learn to rank 的基本框架</h2><hr>
<h1 id="2-L2R数据集"><a href="#2-L2R数据集" class="headerlink" title="2 L2R数据集"></a>2 L2R数据集</h1><h2 id="2-1-数据集构建"><a href="#2-1-数据集构建" class="headerlink" title="2.1 数据集构建"></a>2.1 数据集构建</h2><h2 id="2-2-公开数据集"><a href="#2-2-公开数据集" class="headerlink" title="2.2 公开数据集"></a>2.2 公开数据集</h2><hr>
<h1 id="3-L2R主要算法"><a href="#3-L2R主要算法" class="headerlink" title="3 L2R主要算法"></a>3 L2R主要算法</h1><h2 id="3-1-Point-Wise"><a href="#3-1-Point-Wise" class="headerlink" title="3.1 Point Wise"></a>3.1 Point Wise</h2><h2 id="3-2-Pair-Wise"><a href="#3-2-Pair-Wise" class="headerlink" title="3.2 Pair Wise"></a>3.2 Pair Wise</h2><h2 id="3-3-List-Wise"><a href="#3-3-List-Wise" class="headerlink" title="3.3 List Wise"></a>3.3 List Wise</h2><hr>
<h1 id="4-L2R的评价指标"><a href="#4-L2R的评价指标" class="headerlink" title="4 L2R的评价指标"></a>4 L2R的评价指标</h1><h2 id="4-1-Recall-amp-Precision"><a href="#4-1-Recall-amp-Precision" class="headerlink" title="4.1 Recall&amp;Precision"></a>4.1 Recall&amp;Precision</h2><h2 id="4-2-AP-amp-MAP"><a href="#4-2-AP-amp-MAP" class="headerlink" title="4.2 AP&amp;MAP"></a>4.2 AP&amp;MAP</h2><h2 id="4-3-DCG-amp-IDCG-amp-NDCG"><a href="#4-3-DCG-amp-IDCG-amp-NDCG" class="headerlink" title="4.3 DCG&amp;IDCG&amp;NDCG"></a>4.3 DCG&amp;IDCG&amp;NDCG</h2><hr>
<h1 id="5-L2R讨论遗留问题"><a href="#5-L2R讨论遗留问题" class="headerlink" title="5 L2R讨论遗留问题"></a>5 L2R讨论遗留问题</h1><h2 id="5-1-特征构造"><a href="#5-1-特征构造" class="headerlink" title="5.1 特征构造"></a>5.1 特征构造</h2><h2 id="5-2-pair-wise-训练集构造"><a href="#5-2-pair-wise-训练集构造" class="headerlink" title="5.2 pair-wise 训练集构造"></a>5.2 pair-wise 训练集构造</h2><h2 id="5-3-不同Query的模型构建"><a href="#5-3-不同Query的模型构建" class="headerlink" title="5.3 不同Query的模型构建"></a>5.3 不同Query的模型构建</h2>
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  <p><span>本文标题:</span>L2R原理解析</a></p>
  <p><span>文章作者:</span>coderpql</a></p>
  <p><span>发布时间:</span>2021年04月15日 - 19:40:55</p>
  <p><span>最后更新:</span>2021年04月19日 - 14:16:20</p>
  <p><span>原始链接:</span><a href="/blog/2021/04/15/L2R%E5%8E%9F%E7%90%86%E8%A7%A3%E6%9E%90/" title="L2R原理解析">http://coderpql.gitee.io/2021/04/15/L2R%E5%8E%9F%E7%90%86%E8%A7%A3%E6%9E%90/</a>
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